PERFORMANCE EVALUATION OF

AIR CLEANING/PURIFICATION DEVICES FOR

CONTROL OF VOLATILE ORGANIC COMPOUNDS IN INDOOR AIR

 

Investigator: Wenhao Chen (wchen13@syr.edu),

Dr. J.S. Zhang (PI), Dr. Z. Zhang, and J.F. Smith

 

June 10, 2004

 

 

EXECUTIVE SUMMARY

 

Poor indoor air quality (IAQ) can significantly affect people’s health, comfort, satisfaction and productivity. Air cleaning/purification devices have held a substantial market for use in residences and offices for removing various contaminants indoors. In recent years, more and more air cleaning devices are advertised in the market for removing chemical pollutants such as volatile organic compounds (VOCs) and for odor control.  However, there is limited information available regarding their performance beyond the general claims of the manufacturers and there are no standard methods for testing the removal efficiency of air cleaning devices for VOCs.

 

In this project, fifteen air cleaning/purification devices have been evaluated for their initial effectiveness in removing VOC contaminants. Twelve of the fifteen devices are portable room air cleaners and three are in-duct devices.  Thirteen are off-the-shelf commercial products, and two are prototypes of innovative products. These products employ different gas-phase contaminant removal technologies, including sorption filtration, UV-photocatalytic oxidation (UV-PCO), ozone oxidation, air ionization (plasma decomposition), and botanical air cleaning.

 

All the products were tested with a mixture of 16 representative VOCs (17 VOCs in tests for products associated with ozone generation) by using a “pull-down” test method in a full-scale stainless steel chamber (16 ft x 12 ft x 10 ft high).  The test VOCs selected cover the wide range of VOC types and vapor pressures typically encountered indoors. Three selected devices were also tested with toluene and formaldehyde by using a “constant source” test method.  Other important parameters, including ozone emission, power consumption, noise level, and pressure drop across the in-duct device, were also measured. The influence of flow rate on the performance of air cleaner was investigated. The effectiveness of using current air cleaning devices for IAQ control were compared with source control and ventilation strategies, and the associated energy costs were also estimated compared between air cleaning and ventilation.

 

The major findings are:

 

(1)   Sorption filtration is still the most effective off-the-shelf commercial technology, at least initially, for general removal of indoor gaseous pollutants. For all sorption-based products tested, significant removal efficiencies were observed for most test VOCs (except dichloromethane, formaldehyde, and acetaldehyde). The light and very volatile gases, such as dichloromethane, formaldehyde, and acetaldehyde, could not be efficiently removed by activated carbon only. However, the removal efficiencies for these gases could be improved if specific sorption media (e.g., activated alumina impregnated with potassium permanganate) are added. More researches are needed to investigate the long-term performance of sorption type devices. The “constant-source” test method with extended test period or some model-based testing method could be used.

 

(2)   For sorption-based products, the removal efficiencies and clean air delivery rates (CADRs) varied a lot from product to product. The sorption filter design plays an important role.  In general, the filters, which could provide more surface area and better contact between contaminated airflow and the adsorbent granular, had higher efficiencies. In addition, the removal efficiencies varied significantly with the properties of VOCs. The general trend was that the efficiency increased with the increase of molecular weight or boiling point of the compound, and decreased as the vapor pressure of the compound increased. However, the relationship was not linear but a stepwise one.  A reasonable good estimation of the removal efficiency can be made for the relatively heavier compounds (i.e., VP < 26 mmHg at 23oC) by using toluene as the single test VOC.  

 

(3)   UV-PCO is an attractive technology because it appears to convert most VOCs into CO2 and H2O under typical indoor concentration levels, and requires no replacement or regeneration of filters as in sorption-based products. Our test results show that a properly designed UV-PCO device (P15, which is a prototype and not yet available commercially) had removal efficiencies competitive to sorption-based devices. Only one byproduct with significant amount was detected by an ATD-GC/MS analysis under test conditions. However, the commercialization of this technology as room air cleaners is still in the beginning stage. The off-the-shelf UV-PCO-based air cleaners did not perform well due to poor product designs. The key issue for the successful commercialization seems to be the improvement of overall quantum efficiency through optimization of the air flows and UV light irradiation on catalytic surfaces as well as improvement of the catalyst. Test results also suggest that the interference effect among different VOCs should be considered even under indoor contaminant concentration levels.

 

(4)   It is not recommended to use room air cleaners that either intentionally generate ozone or produce ozone as a byproduct for indoor VOC control purpose. Such “room air cleaners” include ozone generators and ionizers. Although this type of products may be very quiet and use less power, their removal efficiencies for most indoor VOCs cannot compete with even moderate ventilation (e.g., 0.1 ACH) and they are likely to lead to unsafe ozone concentration level.

 

(5)   The flow rate setting (Qcl) has effects on the performance of air cleaning devices. For each portable air cleaner tested, the power consumption and noise level increased as the set operation level (flow rate) increased.  In general, the overall performance of the cleaner (characterized by CADR) increased as the flow rate increased, although the single pass removal efficiency (h) decreased as the flow rate increased.   The CADR is the combined effect of a decrease in h and an increase in Qcl. The improvement in the overall performance (i.e., CADR) due to the increase in flow rate varied from product to product. It depends on the rate-controlling step of the process, which is influenced by factors such as flow characteristics, product structure, adsorbent or catalyst property, and VOC properties. The improvement was significant for product P2, a sorption-based product, but was much smaller for product P15, a UV-PCO product.

 

(6)   The “pull-down” test method is applicable for comparing and rating the initial VOC removal characteristics between different room air cleaners. The key experimental parameters (i.e., the number of injected VOCs, target VOC initial concentration levels, test period) and the data analysis procedure need to be specified for the method to be a standard test method similar to ANSI/AHAM Standard AC-1-2002.

 

(7)   The effectiveness of air cleaning, when compared with the other IAQ control strategies (i.e., ventilation and source control), may be different from compound to compound even for the same house. Having the range of CADRs obtained for each compound from this project, the relative effectiveness of each control strategy can be compared for a given house under both steady state and dynamic conditions. When the associated energy costs are also considered, it is found that use of the air cleaner with best or medium performance can have significant annual energy savings compared to ventilation.  However, the annual cost savings are much smaller and it may cost slightly more than ventilation even for the best available portable air cleaners for a cold climate condition due to the higher cost of electricity used for the air cleaner than the natural gas for the furnace heater.

 

Further research needs include: (1) integration of the performance data of air cleaning devices into the building system design in conjunction with source control and ventilation strategies for IAQ, and (2) development of computer simulation models for design optimization and performance prediction of air cleaning devices under multiple VOCs conditions.